Do You Want to Learn How to Make Statistical Graphics?

If you’re interested in learning how to use R for statistical graphics or tools like GGobi for exploratory data analysis, check out this workshop in Washington, DC during the end of July right before the annual Joint Statistical Meetings. The workshop’s called Looking at Data.

Graphics are a fundamental part of data analysis, used in initial data inspection and exploration, model building and checking and also communicating information. In this course we will teach the basics of static graphics and move on to the new developments in direct manipulation and dynamic graphics that facilitate exploratory data analysis. The methods taught are readily available in open source software, enabling all participants to reproduce, extend and use them with their own data after the workshop.

This workshop will be focused on the analytical side of things (after all, three statisticians are running it) with static graphics on day 1 and dynamic graphics on day 2, so if you’re interested in learning graphics for analysis, this should be fun.

6 Comments

It’s a bit frustrating that interesting events like these are often organised in combination with a statististical conference. A *lot* of scientists in various fields could equally benefit from this, but often haven’t got the opportunity to go to these conferences since they’re a bit too specialized to justify the scientist’s attendance.

@wwwald: well what scientific conference would you like to see us at? The JSM is relatively low-risk for us since we’re all going anyway, so we don’t need to worry about covering travel expenses etc. We would like to offer more courses in more locations, but we need some assurance that people will actually come!

@Hadley:
Well, the field I’m working in is exposure modelling and environmental risk analysis. Typical conferences are in the fields of epidemiology (ISEE[1] conferences, for instance) or exposure analysis (ISES[2] conferences are an example).

This is a field where large integrated models are set up, often based on point estimates and threshold values. Of course, a trend towards a decent, statistically sound approach is inevitable but data are sparse and there’s a lot left to learn.
I think it would be a great opportunity to get these communities to know R, before they completely jump on a range of proprietary tools and formats, hampering efficient interaction and exchange right from the start…

Well, there you have it :-) I’m not saying it’s up to you to start organising courses on conferences in every field imaginable. But if anything, there are a lot of opportunities out there for plugging R…

Probably I should just invest in expanding my R background and advocate as much as possible :-)